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comparing our experimental observations to predictions made using the Standard Model of Particle Physics. I am a member of the LHCb collaboration, one of the four large experiments at the Large Hadron
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supervisory team from La Trobe University and Sheffield Hallam University, gaining expertise in data-driven performance analysis, statistical modelling and machine learning. This research will enhance our
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@rmit.edu.au to express interest in the project/scholarship. Electrical network modelling Electricity market modelling Power system economics Tariff design Electrical network modelling Electricity market
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to apply: Seismic wave propagation theory; seismic data acquisition and processing; signal processing, seismic imaging, geophysical inversion, scientific programming, reservoir modelling. Previous research
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of English proficiency may be required. The project will provide numerous research and development opportunities including: Development of phenomenological and CFD models for aeration systems of sewage
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, the internal workings of deep neural networks remain largely mysterious, posing a significant challenge to the interpretability, reliability, and further advancement of these models. This project seeks deep
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the development of numerical methods for astorphysical fluid dynamics and radiation transport. Projects may employ a range of approaches from analytic modelling and numerical calculations on desktop
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My research interests focus on the stars - primarily their structure, evolution and nucleosynthesis. This can involve modelling of mixing in stars, or effects of changing nuclear burning rates
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I supervise a wide range of projects stellar astronomy. They include modelling stars in 1D or 3D, deciphering the origin of the elements (stellar nucleosynthesis), and observing using optical
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interesting implications for standard models of hierarchical black hole growth. Aims This project aims to explore the optical/IR properties of the most extreme IFRSs, and confirm their redshift range